Traditionally, businesses have had access to certain types of information that they use to make important business decisions, such as whether and where to build new retail stores or how best to allocate marketing dollars to certain types of customers, business segments, or geographies. Such investments can be substantial and can result in significant losses if underlying assumptions prove to be inaccurate. With the increasing volume and availability of digital information, opportunities exist for improved data analysis. However, the mere existence of voluminous amounts of data does not translate into better business decisions. It is generally advantageous or necessary to selectively identify and process the data in order to provide an improved predictive result. Exemplary embodiments of the present invention address this need and can provide advantages to businesses in making decisions regarding investments, promotions, day-to-day operations management decisions, and other transactions.